Without clinical documentation that correctly captures the complexity and nuance of a patient’s diagnosis, important metrics – like the quality of patient care and the accuracy of reimbursement rates – can easily suffer. But why is it such a challenge to ensure that clinical notes meet this standard?
Physicians lack time to manually validate diagnoses
A February 2020 study published in the Annals of Internal Medicine concluded that, on average, physicians spend roughly 16 minutes engaging with electronic health records (EHRs) for every patient visit. And chart review (33%), documentation (24%), and ordering (17%) functions account for most of that time.
We know that physicians spend a lot of time looking at screens – roughly twice as much time is spent on administrative work over direct patient care. But the time crunch at the patient encounter, along with poor interoperability across the healthcare ecosystem, still means providers don’t have a lot of time to ensure accurate clinical documentation in their day-to-day work.
Patient care and reimbursement rates are suffering
But as the Centers for Medicare & Medicaid Services’ (CMS’) Evaluation and Management Services Guide shows, high-quality clinical documentation is chiefly important in healthcare. Indeed, as CMS states, “Clear and concise medical record documentation is critical to providing patients with quality care and is required for you to receive accurate and timely payment for furnished services. Medical records chronologically report the care a patient received and record pertinent facts, findings, and observations about the patient’s health history. Medical record documentation helps physicians and other health care professionals evaluate and plan the patient’s immediate treatment and monitor the patient’s health care over time.”
The guide’s seven actionable principles for healthcare providers responsible for clinical documentation are as follows:
- The medical record should be complete and legible
- The documentation of each patient encounter should include:
- Reason for encounter
- Relevant history
- Physical exam findings
- Diagnostic results
- Clinical assessment and impression
- Plan of care
- Clarity about date and rationale for ordering diagnostic tests should be easily inferred
- Past and present diagnoses should be accessible to the physician
- Appropriate health risk factors should be identified
- The patient’s progress, response to and changes in treatment, and revision of diagnosis should be documented
- The diagnosis and treatment codes reported on the health insurance claim form or billing statement should be supported by documentation in the medical record
That’s a long list for physicians to step through in a few minutes. And, of note, language about recording diagnoses shows up four times.
Risk adjustment is falling short – and health plans care
Under a fee-for-service (FFS) payment model, healthcare providers and health plans focus attention on ensuring accurate procedure coding. Reimbursements match services provided. Risk-based payment arrangements – like Medicare Advantage (MA) or Accountable Care Organizations (ACOs) – however, also require comprehensive diagnosis coding to power risk adjustment.
If diagnoses are inappropriately absent from patient charts and claims, risk profiles scores will inevitably fall short and health plans and providers will not be fairly compensated for caring for sicker patients. Therefore, many ACO contracts or MA programs employ nurses or outside firms to identify and document missing or inaccurate diagnoses codes to increase capitated payments. This retrospective path is seen as an easier and quicker path to increased payments, as it may not require physician action, but it comes with a high price tag.
Downstream clinical research is hindered
Finally, digital patient records have facilitated the construction of large, population-based patient databases with enormous potential for epidemiological and clinical research. However, if data isn’t captured at the point of care, it undermines statistical power and selection bias.
Without efficient clinical workflows and clean, insightful problem lists supported by granular clinical terminology, documentation at the point of care becomes a challenge – and that leads to a host of other issues throughout the healthcare ecosystem.
